An IOT Based Low Power Health Monitoring with Active Personal Assistance

1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume 4 Issue 1, December 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470 An IOT Based Low Power Health Monitoring with Active Personal Assistance B. N. Meenakshi1, Mrs. N. V. Durga2 1M.Tech Scholar, 2Assistant Professor, 1,2V. S. Lakshmi Engineering College, Matlapalem, Andhra Pradesh, India ABSTRACT Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. A lot of research has been going on continuous home and personal monitoring applications. There are many solutions were adapted by these technologies to make better remote monitoring applications. The traditional continuous home and personal monitoring systems which are implemented with traditional client-server architecture which may fail in factors like low power consumption, un- deterministic data delivery time, More sensitive to external connectivity issues (temporary failures of servers), adhoc networks (using ZigBee and Z-wave etc.) and also increase the cost of implementation. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance for active and assisted Living (AAL) joint program. With advent of cloud services, the continuous remote monitoring based applications became truly “plug-and-play” approach implementation and also reduce the problems of temporary failures. One of the biggest challenges in this area is to make such application devices work with low power (battery based applications). The main drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. In this project, a solution is proposed to improve the low power consumption in Wi-Fi sensors by making use of advanced RF based Microprocessor from Texas instruments (CC3200). Bed Occupancy sensor automation has been designed and implemented to test the feasibility of the approach. The TI CC3200 comes with ARM-Cortex-M4 as a core and inbuilt Wi-Fi subsystem. The CC3200 provides different power modes to make the device enter into sleep or hibernate mode. This device will only enter only in work phase when the sensor is active state. During this phase, the processor sample and processes the sensor data and uploads to the cloud using REST API. Thing speak is an IoT cloud service used to present the sensory data as graphs, bar charts, and dashboards on the cloud remaining time it will enter into sleep phase to save the power of the device, so that it will extend the battery life time of the device. KEYWORDS: SoC, WBAN, IoT, Rest, AAL, ZigBee I. INRODUCTION The average population age [1] has been increment in a progressive manner, which has a deep social and economic impact, most importantly. The effects of social and healthcare policies between younger and older class-ages creating a progressive imbalance, questioning the sustainability of long-established welfare models. Reducing the need of social and health-care services currently associated with aging is a primary goal, in order to preserve quality of life of aging population in an affordable way. The current popular Communication technologies may contribute to the development of active aging scenarios [2], and are at the core of many worldwide research initiatives and programs. Among them, the “active and assisted Living joint program” (AAL-JP) [3] is exploring opportunities fostered by Communication and Information Technologies to improve the conditions of life for older adults. How to cite this paper: B. N. Meenakshi | Mrs. N. V. Durga "An IOT Based Low Power Health Monitoring with Active Personal Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1, December 2019, https://www.ijtsrd.com/papers/ijtsrd29 603.pdf Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC (http://creativecommons.org/licenses/by /4.0) IJTSRD29603 pp.486-489, URL: BY 4.0) The implementation age-friendly home environments is a relevant goal: concepts such as smart homes [4]–[6], ambient intelligence [7], telemedicine [8], [9], and telemonitoring [10]–[12] converge in such a perspective. Key enabling technologies include sensing, reasoning, communicating, and interacting components. In order to be effective, deployment of ICT solutions within the home environment should not be perceived as intrusive, should not require bothersome changes in lifestyles and habits and needs to be accessible and trustworthy to (possibly unskilled) older adults. This scenario introduces stringent and peculiar design constraints. According to people-centric paradigms we describe how the above concepts have driven the evolution of “smart home” systems. Based on such experiences, we focus here on the need of solutions being reliable, inexpensive, easy to deploy and maintain, interoperable and highly customizable (for personalization and managing of needs evolving over time).A and Information @ IJTSRD | Unique Paper ID – IJTSRD29603 | Volume – 4 | Issue – 1 | November-December 2019 Page 486

2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 promising AAL objective consists of the exploitation of data coming from the home environment (through nonintrusive sensors) for the inference of “behavioral” data patterns, possibly meaningful in evaluating risk conditions or needs related to health and well-being. For instance, behavioral remote monitoring is expected to be most relevant in early assessment and identification of dementia and in the related safety provision [15]. In order to implement low cost and low power AAL based age-friendly home environments, the requirement of making use of low power Source technology. With the advent of miniaturization of SOC chip technology, chip manufacturing companies have been developing high performance digital microcontroller along with inbuilt Wi-Fi technology for the development of it.The Texas Instruments (TI)company developed a low cost, high speed and low power microcontrollers (named simple link wireless MCUs – CC3200) as SoC with a size 9mmx9mm. In this project, CC3200 is used as independent wireless sensor nodes for developing the application as per requirement. This CC3200 SoC comes as an integration of Wi-Fi-module along with ARM-Cortex M4 digital processor. This chip also has analog sub modules like, programmable comparator, and Analog to Digital converters. A cloud based application is developed to monitor and display the information coming from CC3200 sensor node [5]. The rest of the paper is organized as follows. Section II describes the proposed system related work of this paper. Section III presents the overall architecture and complete block diagram of proposed system for this project. Section IV presents the software and hardware implementation of the proposed system. Section V presents the results of hardware and BED Occupancy sensor which is on the Things Speak cloud service of this paper. Section VI provides the conclusion of the paper. II. The present research on active and assisted living focusing on home-monitoring systems have been reported in [18]- [20] by. Such systems use a large number of different sensors to track the daily activities. In figure 1, a generic architecture of the home-monitoring is shown figure 1. Referring to different variety of classes of home sensors, a home gateway, which stores, aggregates, and processes sensor data, and an Internet gateway providing access to cloud-based services like thing speakexcite, etc. Deploying the sensor based network in a user’s home is a highly demanding design task, due to the non-intrusiveness, usability, and acceptability concerns mentioned in the introduction above: initially, home sensor systems-based there connectivity over wired technologies, exploiting either proprietary protocol [21]–[23] (E.g., X10, KNX, and LON), or open standards such as Ethernet [24]. With the advent of Wireless communication the connectivity of the home sensor network is providing much higher flexibility and installation ease, at the expense of some delicate design issues, dealing with the propagation of radio signals within a built environment. Also, some maintenance tasks are introduced (checking and replacing/recharging batteries, for battery- operated devices). In this case too, a number of different varieties of technologies have been introduced: among the most diffused, Bluetooth is mostly exploited for short-range communication (e.g., body area networks (BAN)) whereas Z- wave [25] and ZigBee [26]–[28], protocols (among many others) have emerged as most practical options for the implementation of a home sensor network. III. PROPOSED SYSTEM ARCHITECTURE The proposed system active and assistive home monitoring is shown in figure 2. PROPOSED SYSTEM Figure3: Implemented block diagram Proposed System for active-assisted living The proposed system architecture is a single System on Chip (SoC) and Wi-Fi connectivity can be used to monitor all the normal human vitals and directly send such information to web services without using any personal servers. The recent advancements in Wi-Fi technology will allow the Wi-Fi devices to operate with low power. So by using this IP based multiple sensor node instead of multiple BIN’s will reduce the cost and power requirement for remote heath monitoring systems. Because of the Internet of Things, the multiple sensor data from proposed device can be viewed from anywhere and anytime. The proposed system consists of i) Bed-Occupancy Sensor, which converts the analog pressure into analog voltage. ii) Sampling and ADC section, which converts analog electrical Figure1: AAL Based Wi-fi home monitoring system Figure2: A simple model of Existing System architecture for active-assisted living. @ IJTSRD | Unique Paper ID – IJTSRD29603 | Volume – 4 | Issue – 1 | November-December 2019 Page 487

3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 ?It has operating supply voltage of 3v and operating temperature of -10c to +60c. ?1.3-inch display screen has the resolution of 96x96 pixels (9216 pixel stripe array) ?Display control can be controlled by serial peripheral interface protocol (SPI) ?Typical power consumption of the display module 6uW - 10uW(static mode, depends on update rate) signals to digital signals, which in turn processed by the high performance digital ARM microcontroller. iii) The ARM microcontroller processes the digital data and converts internet IPv6 data packets. iv) The wireless transceiver module allow the device to get connect to router. IV. PROPOSED SYSTEM IMPLEMENTATION The working of the proposed system implementation is divided into three parts. Since the embedded processor used in this device runs with Real Time Embedded Operating System. The following sections will be executed as an independent parallel task in the processor itself using real time operating system. 1.Bed-Occupancy Sensor 2.Display Section (LCD Booster pack) 3.Processing Section 4.IoT Connectivity 1.Bed-Occupancy Sensor: The bed occupancy sensor consists of a bed pressure pad [49], which is placed underneath the mattress of the user. The pressure sensor behaves as a variable resistor, lowering its resistance value when pressed. It is therefore connected as a pull-down element in a voltage divider, the output of the pressure sensor is connected to an analog input of the microcontroller hardware board. The long cable features a plug and play connector, to avoid tearing off the cable (for instance while making the bed). An additional digital input, therefore, comes from the cable connector, to signal a fault condition (disconnected pad). Furthermore, the battery voltage is transmitted, to allow for remote maintenance tasks. The chair occupancy sensor works in the same way, consisting of chair pressure pad in order to provide a complete occupancy solution. Figure5: LCD booster pack 3.Processing section: TheCC3200 launch pad is a low cost evalution platform for ARM cortex-M4 processor, which process the Bed- Occupancy sensor and temperature samples and converts them into digital values using its internal 12-bit ADC. The ARM processor further process the ADC values and then converts them as TCP packets, which can be easy to send via internet using TCP/IP reference model. This CC3200 launch pad also comes with integrated temperature sensor TMP006, these temperature values taken as body temperature and sends it to the network. 4.IoT Connectivity: The CC3200 launch pad board comes with integrated on- chip Wi-Fi module. This Wi-Fi module consumes very low power during the transmission/reception of the wireless data. It's just to program as station mode to connect to home router, which in turn connects to internet. Alternatives to ThingSpeak are Android Things, Beebotte, DataGekko etc. ThingSpeak portal is an IoT cloud based services, where we can upload the sensor data and plot that data as graphs and bar charts. Through programming, it's possible to configure to different cloud based services. V. RESULTS The Proposed System implementation show in figure6, the right side of the figure shows the pressure sensor. Bottom red color board of the figure is CC3200 MCU launch pad board, which is it consists of ARM cortex--M4 processor and on-chip Wi-Fi module. The display (96x96 LCD booster pack) showing message about the IoT cloud (Thingspeak) connectivity. Fig Figure 4: Bed-Occupancy Sensor. 2.The Display Section: The Sharp Memory LCD Booster Pack display module comprised of 96x96 pixels to render of smooth-moving graphics with 50% reflectance as shown in figure 5. We will give the operating supply voltage from 3v to 5v.This display is based on the LS013B4DN04 display and comes as a plug and play module, so CC3200 Launch Pad Evaluation Kit programmers can use this readymade Booster Pack to display analog sensor readings, time & other related information. This display will consume low power use of 10uW. The booster pack LCD is visible in a 0.5-lux environment without requirement of external light source. ?A Reflective panel of the display comes as white and black with aspect ratio of 1:1 Figure6: Hardware implementation of proposed system (CC3200, LCD Booster Pack, Pressure sensor). @ IJTSRD | Unique Paper ID – IJTSRD29603 | Volume – 4 | Issue – 1 | November-December 2019 Page 488

4. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 The figure 7 showing both temperature and bed occupancy sensor data on the display and at the same time on the Thinks peak IoT cloud based service as shown in figure 9. Here the field1 represents the temperature data and field2 represents Bed Occupancy data. Figure9: shows the both temperature and bed occupancy data wave forms on Things peak cloud. VI. In this paper, CC3200 MCU Launchpad is the one of the best suitable processor for development of active and assisted living for home automation. The Integration of ARM cortex M4 processor and on-chip Wi-Fi module will reduce the space and wiring connections. At the same time, everything wills ease configured. As the results shows, it will take very less power and available in reasonable price which is main requirement for AAL. REFERENCES [1]World Health Statistics 2016: Monitoring Health for the SDGs, WHO Report. Accessed: Sep. 2017. [Online]. Available:http://www.who.int/Gho/publications/worl d_health_statistics/2016/en/ CONCLUSION Figure7: Temperature and Bed Occupancy data The below figure 8 shows the amount of current in mill- amperes is shown, the system connecting with cloud based services. Therefore, the entire system will consume a maximum of 2mA current while transmitting the data to cloud. Because of this, CC3200 is the most suitable processor module for developing Active and Assisted Living Home Automation. [2]C. Siegel and T. E. Dorner, “Information technologies for active and assisted living—Influences to the quality of life of an ageing society,” Int. J. MED. Inform., vol. 100, pp. 32–45, Apr. 2017. [3]AAL Programmed Website. Accessed - Sep, 2017. [Online]. Available: http://www.aal-europe.eu/ [4]L. Liu, E. Stroulia, J. Nikolaidis, A. Miguel-Cruz, and A. R. Rincon, “Smart homes and home health monitoring technologies for older adults: A systematic review,” Int. J. MED. Inform., vol. 91, pp. 44–59, Jul. 2016. [5]G. Sprint, D. J. Cook, R. Fritz, and M. Schmitt- Edgecombe, “Using smart homes to detect and analyze health events,” Computer, vol. 49, no. 11, pp. 29–37, Nov. 2016. [6]R. Li, B. Lu, and K. D. McDonald-Maier, “Cognitive assisted living ambient system: A survey,” Digit. Common. Netw. Vol. 1, no. 4, pp. 229–252, Nov. 2015. Figure8: The amount current consuming by the system when connecting with cloud based services The figure 9 shows, live data plotting on the Things peak IoT cloud based services. The right side graph is for bed occupancy and left one is temperature data. [7]D. J. Cook, J. C. Augusto, and V. R. Jakkula, “Ambient intelligence:- Technologies, opportunities,” Pervasive Mobile Comput., vol. 5, no. 4, pp. 277–298, Aug. 2009. applications, and [8]M. Krol, “Telemedicine,” IEEE Potentials, vol. 16, no. 4, pp. 29–31, Oct. 1997. @ IJTSRD | Unique Paper ID – IJTSRD29603 | Volume – 4 | Issue – 1 | November-December 2019 Page 489